Downscaling Nonstationarity: Process-Based Evaluation of Temperature and Precipitation Projections and Downscaling Methods Over the CONUS: Charting a Path for End-Users from the CMIP6 Ensemble to Multivariate Facility-Level Risks

Abstract

There is a critical need for granular information on how surface temperature and precipitation statistical distributions will change across the Conterminous United States (CONUS) at the DoD Facility Level throughout the 21st Century. Ensuring resilience for infrastructure and operations in the face of nonstationarity, where surface conditions that occurred in the past may not encompass the range of conditions in the future, requires this information. Unfortunately, the primary tools for developing projections of future surface temperature and precipitation, Earth System Models (ESMs), are producing overwhelmingly large datasets that both disagree with each other at the regional level and do not resolve the hydroclimate processes that are most likely to impact Facilities . Therefore, the primary objective of RC19-1391 is to develop localized, accessible surface temperature and precipitation projections, along with their uncertainties, using state-of-the-science information from ESMs.

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Document Details

Document Type
Technical Report
Publication Date
Aug 22, 2022
Accession Number
AD1217024

Entities

People

  • Daniel R. Feldman
  • Dominic M. Di Toro
  • Herbert E Allen
  • Jimmy M. Gelvez
  • Kevin P Hickey
  • Paula C. Hernandez
  • Pei Chiu
  • Richard F. Carbonaro

Organizations

  • University of California, Berkeley
  • University of Delaware

Tags

DTIC Thesaurus Topics

  • Civil Engineering
  • Climate Change
  • Computational Science
  • Data Science
  • Earth Sciences
  • Engineers
  • Geography
  • Greenhouse Effect
  • Greenhouse Gases
  • Information Science
  • Jet Propulsion
  • Meteorology
  • North America
  • Statistical Distributions
  • Statistics
  • Surface Temperature
  • United States

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Systems Analysis and Design